Question

我有以下查询：

SELECT 
   START_DATE
  ,ID
  ,USER
  ,ROW_NUMBER(PARTITION BY USER ORDER BY START_DATE) AS RN

FROM TABLE

带来以下结果：

START_DATE   ID   USER   RN
2019-01-01   200  01     1
2019-01-10   450  01     2
2019-01-02   500  02     1

我只想显示具有多个开始日期（第1、2、3行）的用户，并排除仅具有row_number为1的用户。其次，我需要在每个DATEDIFF()之间显示Row_Number。

我本以为将ROW_NUMBER包括在内，但不知道该怎么做。它可能需要一个新的解决方案。如下所示：

START_DATE  USER   datediff
2019-01-01  01     10

Answer 1

WITH TMP AS (
    SELECT 
       START_DATE
      ,ID
      ,USER
      ,LAG(START_DATE) OVER ( PARTITION BY USER ORDER BY START_DATE) AS LAST_START_DATE
      ,CASE WHEN MIN(START_DATE ) OVER ( PARTITION BY USER ) = 
                 MAX(START_DATE) OVER ( PARTITION BY USER) THEN 1
            ELSE 0
        END ExcludeIfOnlyNonUnique
      FROM TEST_DATA)
SELECT TMP.START_DATE,
       TMP.ID,
       TMP.USER,
       DATEDIFF(TMP.START_DATE, TMP.LAST_START_DATE) START_DATE_DIFF
  FROM TMP
 WHERE ExcludeIfOnlyNonUnique = 0;

Answer 2

有许多方法可以做到这一点，但是更优雅的方法之一是使用Microsoft SQL Server函数的领先和落后。这些函数使您可以通过方法访问分区中前一行和后一行中的值。在这里阅读它们：

领导：https://docs.microsoft.com/en-us/sql/t-sql/functions/lead-transact-sql?view=sql-server-2017

滞后：https://docs.microsoft.com/en-us/sql/t-sql/functions/lag-transact-sql?view=sql-server-2017

Answer 3

我将使用CTE并两次加入查询。

WITH MY_QUERY AS (
  SELECT 
    START_DATE, 
    ID, 
    USER,
    ROW_NUMBER(PARTITION BY USER ORDER BY START_DATE) AS RN
  FROM SOMETABLE
), MY_ID AS (
  SELECT DISTINCT USER FROM MY_QUERY
)
SELECT Q1.START_DATE, Q1.USER, DATEDIFF(Q1.START_DATE, Q2.START_DATE) AS DIFF
FROM MY_ID ID
JOIN MY_QUERY Q1 ON ID.USER = Q1.USER AND Q1.RN = 1
JOIN MY_QUERY Q2 ON ID.USER = Q2.USER AND Q2.RN = 2

Answer 4

在脚本下方尝试此操作-

WITH CTE(START_DATE, ID, [USER], RN)
AS
(
    SELECT 
    START_DATE
    ,ID
    ,USER
    ,ROW_NUMBER(PARTITION BY USER ORDER BY START_DATE) AS RN
)

SELECT MIN(START_DATE) [START_DATE], 
[USER],
DATEDIFF(DD,MIN(START_DATE),MAX(START_DATE))+1 [datediff]
FROM CTE
GROUP BY [USER]
HAVING MAX(RN) > 1

Answer 5

您不希望import numpy as np meanvec_obama = np.array(wordvecs_obama).mean(axis=0)。您要row_number()：

count()

如果仍然需要，您可以在结果集中添加select t.* from (select . . . , count(*) over (partition by user) as cnt from t ) t where cnt > 1;。

DATEDIFF（）具有不同ROW_NUMBER的日期之间

5 个答案: